Article pubs.acs.org/est
Atmospheric Reactive Nitrogen in China: Sources, Recent Trends, and Damage Costs Baojing Gu,†,‡ Ying Ge,‡,§ Yuan Ren,‡ Bin Xu,∥ Weidong Luo,†,§ Hong Jiang,⊥ Binhe Gu,# and Jie Chang*,‡,§ †
College of Economics, Zhejiang University, Hangzhou 310027, People's Republic of China College of Life Sciences, Zhejiang University, Hangzhou 310058, People's Republic of China § Research Center for Sustainable Development, Zhejiang University, Hangzhou 310058, People's Republic of China ∥ Department of Public Administration, Zhejiang Gongshang University, Hangzhou 310018, People's Republic of China ⊥ International Institute for Earth System Science, Nanjing University, Nanjing 210093, People's Republic of China # Soil and Water Science Department, University of Florida, Gainesville, Florida 32611, United States ‡
S Supporting Information *
ABSTRACT: Human activities have intensely altered the global nitrogen cycle and produced nitrogenous gases of environmental significance, especially in China where the most serious atmospheric nitrogen pollution worldwide exists. We present a comprehensive assessment of ammonia (NH3), nitrogen oxides (NOx), and nitrous oxide (N2O) emissions in China based on a full cycle analysis. Total reactive nitrogen (Nr) emission more than doubled over the past three decades, during which the trend of increase slowed for NH3 emissions after 2000, while the trend of increase continued to accelerate for NOx and N2O emissions. Several hotspots were identified, and their Nr emissions were about 10 times higher than others. Agricultural sources take 95% of total NH3 emission; fossil fuel combustion accounts for 96% of total NOx emission; agricultural (51%) and natural sources (forest and surface water, 39%) both contribute to the N2O emission in China. Total atmospheric Nr emissions related health damage in 2008 in China reached US$19−62 billion, accounting for 0.4−1.4% of China’s gross domestic product, of which 52−60% were from NH3 emission and 39−47% were from NOx emission. These findings provide policy makers an integrated view of Nr sources and health damage to address the significant challenges associated with the reduction of air pollution.
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INTRODUCTION Human activities have more than doubled the global rates of preindustrial nitrogen fixation in terrestrial ecosystems through the Haber−Bosch process, fossil fuel combustion and legume cultivation.1 Although this enhanced nitrogen fixation has promoted the production of food, fiber, and energy, the low nitrogen use efficiency (NUE) also has led to over 50% of the total reactive nitrogen (Nr) load, or about 60−100 Tg N yr−1 globally, being emitted to the atmosphere2,3 and posed important and growing impacts on human and ecosystem health.4 However, considerable uncertainty remains in our knowledge of the sources, magnitude, and spatiotemporal changes of the atmospheric Nr fluxes.2 Previous remote sensing and modeling-based studies have suggested that the variations in atmospheric Nr fluxes are primarily determined by the sources of emission and general atmospheric circulation patterns.5−7 Furthermore, those studies have suggested that sources of Nr to the atmosphere are of different origin (agriculture, fossil fuel, transport, and industry) and are regulated by different factors, such as climate, environment, human activities, economics, and technology.8−10 Thus, © 2012 American Chemical Society
identifying changes in specific sources of Nr emission as well as understanding and quantifying the contribution of human and natural factors to the changes of atmospheric Nr fluxes have been a crucial topic in global biogeochemical research. Serious atmospheric nitrogen pollution has occurred in China, along with the tremendous socioeconomic development since the late 1970s.11 Currently, atmospheric Nr pollution monitoring in China is based on monitoring sites that are mainly located in urban areas, and data of Nr pollution from rural areas are lacking.12 To remedy this deficiency, remote sensing tools are used to measure the changes in air Nr pollution for the entire mainland China.13 However, both of the aforementioned monitoring tools do not track the sources of Nr pollutants and contribute minimally to the development of abatement regulations. Although the global emission inventories, such as EDGAR,14 FRCGC,15 and IIASA,16 include Received: Revised: Accepted: Published: 9420
April 11, 2012 July 21, 2012 August 1, 2012 August 1, 2012 dx.doi.org/10.1021/es301446g | Environ. Sci. Technol. 2012, 46, 9420−9427
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Figure 1. Nitrogen cycle in coupled human and natural systems (CHANS). Arrows represent nitrogen fluxes; solid rectangles represent subsystems and system; dashed lines represent boundaries of functional groups, of which green represents processor, red represents consumer, cyan represents remover, and blue represents life-supporter.
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METHODS Nitrogen Flows from the Land to the Atmosphere. The nitrogen emissions in this study were calculated based on a full cycle analysis, which is a framework to quantify and track the trajectory of all nitrogen fluxes in a CHANS. The CHANS approach seeks understanding of the complexity through the integration of knowledge of constituent subsystems and their interactions.22 This involves linking submodels to create coupled models capable of representing human (e.g., economic, social) and natural (e.g., hydrologic, atmospheric, biological) subsystems and most importantly the interactions among them.10,21 The diagram of CHANS is useful in identifying the crucial system components and flows and the consequences of linkages between subsystems as well as analyzing the role of humans in CHANS (Figure 1). In this study, the CHANS is divided into four functional groups: N-processors, N-consumers, N-remover, and life-supporter, based on the mutual services among these groups (Figure 1), and each functional group includes several subsystems. On the functional groups level, the consumer functional group (mainly human) is the metabolic core of nitrogen cycling in CHANS.23 External nitrogen inputs first go through the processor (e.g., cropland, industry, etc.) for products processing; then, they are transferred to the consumer for consumption, transferred to the remover group (wastewater and garbage treatment) for Nr inactivation, and ultimately, exit the system (Figure 1). Nr from the processer, consumer, and remover functional groups would leak to life-supporter (atmosphere, surface water, and groundwater), reducing the NUE. In particular, the large flux of nitrogen loss from the processer group and the deficiency of Nr removal ability of the remover group greatly contribute to the Nr accumulation in the life-supporter. More details of the nitrogen cycle in a CHANS
China’s data and can identify the emission sources, the nonspecific emission factors (EFs) at the global scale and low spatial resolution result in large uncertainties. To improve the tracking of sources, studies have involved the development of inventories on Nr emissions in China, for example, NOx emission from combustion,13,17,18 NH3 emission from the rural area,12 and nitrous oxide (N2O) emission from some terrestrial ecosystems.7,19,20 However, large variations in atmospheric Nr fluxes of these studies imply that a comprehensive quantification of the sources and causes of the Nr emission for the entire country of China is still a challenge. The primary purposes of this study were to investigate how and why the atmospheric Nr fluxes varied on spatiotemporal scale over the past three decades and how to regulate the related pollutants and reduce health damage costs in China. To achieve these goals, we conducted a full cycle analysis based on coupled human and natural systems (CHANS) approach to cover and integrate all specific Nr emission sources and their interactions. The CHANS approach is an explicit acknowledgment that human and natural systems are coupled via reciprocal interactions, such as material flows.21 It is a comprehensive way to fully analyze the patterns and processes of atmospheric Nr emissions and further assess how human and natural factors affect these patterns and processes. Thus, in this study, we quantified the variations in atmospheric Nr emissions (including NH3, NOx, and N2O) both on temporal (from 1980 to 2008) and spatial (provincial and land use) scales and the causes of variations of Nr fluxes by considering natural and human factors via the CHANS approach. Finally, we assessed the damage costs of Nr emission to human health in China. 9421
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Figure 2. Comparison of our estimates with other studies for NH3 (a,b), NOx (c,d), and N2O (e,f).
Administration (NASA). The band ranges from 270 to 500 nm, with a spectral resolution of about 0.5 nm and a spatial resolution of 24 × 13 km2.25 Raw NO2 column data were processed using Matlab R2007a and then converted to Shape format with geographic coordinates. The inverse distance weighted (IDW) interpolation method was used to interpolate the NO2 data to a tiff format file with a spatial resolution of 0.83° in ArcGIS Desktop 9.2. The NO2 concentration from each province was obtained by weighting all the data within a provincial boundary. Health Damage Costs. Unlike long-lived N2O, which globally mixes in the atmosphere, the formation and health effects of NH3 and NOx are regional and cannot be accurately determined without considering the spatial patterns of emissions relative to population density.26 Generally, the intake fraction (iF) perhaps is the simplest way available to summarize the relationship between the intake of a pollutant and the subsequent exposure to that pollutant or a secondary byproduct.27 The iF is positively correlated to the population density and can provide population-weighted exposures per unit emissions.27,28 Therefore, in this study, we used population density as an indication to estimate the exposures per unit Nr emissions in China. The valuations of human damage cost on the exposures per unit Nr emissions generally were derived from the willingness to pay (WTP) for effects reduction.28−30
as well as among functional groups and subsystems can be seen in the Supporting Information. A mass balance approach is used to quantify the nitrogen fluxes for each subsystem (in total, 14 subsystems in this study) in a CHANS of China with over 6000 nitrogen flows. Data sources were mainly derived from Chinese governmental statistical yearbooks and bulletins that supplied the best available data for anthropogenic nitrogen cycle quantification and from published papers that were used for meta-analysis and comparison. On the basis of the nitrogen balance of the CHANS, we extracted all the Nr fluxes that were emitted from different subsystems to the near-surface atmosphere. The specific sources of each Nr emission item were identified and quantified for different regions and then aggregated on different scales to satisfy the assessment needs. We used the Nitrogen Cycling Network Analyzer (NCNA) model to compile the data set and calculate all the nitrogen fluxes.24 This model can standardize the parameter collections for the nitrogen flux calculations and automatically calculate the nitrogen fluxes and their relationships based on the mass balance approach. More details of data sources and the calculation can be seen in the Supporting Information. Atmospheric Remote Sensing. The tropospheric columns of NO2 were retrieved from the Ozone Monitoring Instrument (OMI), U.S. National Aeronautics and Space 9422
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N in 2005),16 but is much higher than EDGAR (8.4 Tg N in 1995).14 The biggest disparity between our and EDGAR’s estimate is in manure NH3 emission. We estimated 5.2 Tg N, but EDGAR estimated only 2.3 Tg N of NH3 emission from manure management and grazing in 2005. The numbers of animals used in our study and EDGAR were both from FAO,31 suggesting that the relatively low EFs in EDFAR are probably the reason for the disparity. EDGAR adopts IPCC’s EFs of NH3 that are mainly estimated based on the fraction of manure applied to the soil, and this way may underestimate the NH3 emission, since most of the NH3 releases during the fart, storage, transportation, and even runoff to the surface water of livestock excretion.32 Therefore, in this paper, we estimated the NH3 emission based on per capita livestock that can cover all the NH3 emission during the whole lifespan of livestock. Compared to Wang et al.,33 our estimate was higher from 1985 to 1994, while lower from 1995 to 2005. The disparities are mainly attributed to the differences in NH3 emission from livestock (e.g., 5.2 Tg N vs ∼9 Tg N in 2005) caused by the inconsistency in the livestock database (FAO31 for our study versus Chinese agricultural yearbook for Wang et al.33), since the EFs of NH3 of livestock for our study and Wang et al.33 are close. More detailed information can be seen in the Supporting Information. Our estimate of NOx emission is consistent with previous estimates (Figure 2d, Table 1), except that of MEPC,34 in which only fossil fuel combustion was considered. The estimate on NOx emission shows a small variation among this study and previous studies.14−16,35 The small variations of estimates among different studies may be explained by the dominance of fossil fuel combustion as the major emission source, which is responsible for over 96% of total NOx emission in China (Supporting Information, Figure S2) and the small variation of EFs for fossil fuel combustion.13,18 For N2O emission, our estimate is close to other studies7,14 before the 1990s (Figure 2f, Table 1); however, the disparities of estimations among different studies increase since the 1990s. The large variations after the 1990s may be caused by the inconsistencies of estimates on nitrogen inputs to the system,14,16 since the N2O emission is generally positively correlated to the Nr loading.19,20 For example, our estimates of N2O emissions are lower than those of Tian et al.;7 one of the explanations can be that a higher Nr deposition rate (contributing about 30% of total N2O emission in China) used by Tian et al.7 that led to an increase in the estimate of N2O emission from forests in China. Temporal Variations and Future Changes. The emission trends of NH3, NOx, and N2O over the past three decades are different in China (Figure 2). NH3 emission doubled from 1980 to the end of the 1990s, after which the rate of increase apparently slowed down with the formation of a turning point in 1999 (Figure 2a). The turning point emerged is due to the application rates for nitrogen fertilizer (the largest nitrogen input) stopped increasing,36 especially in Eastern China37 (see Figure S2 of the Supporting Information for details. Similarly, the turning point of NH3 emission was also found in Europe,38 the United States,3 and other developed countries in the 1980s owing to the development of precision agriculture that improved the NUE and reduced the nitrogen fertilizer usage.8,39 For example, the NUE of maize production in the United States has increased 36% from the 1980s to the 2000s.40 However, there is still no indication that total NH3 emissions would decline in China without regulations. The
Thus, differences of the WTP between different countries should be considered in the estimates of health damage cost. The most important end point for air pollution by Nr is mortality from chronic exposure (to ozone and secondary particulate matter), which for example, contributes 67% to total health cost in Europe.28 The air pollution mortality should be evaluated in terms of loss of life expectancy rather than of number of premature deaths.29,30 In benefit−cost analyses of environmental programs conducted in UAS and the Europe, loss of life expectancy is typically valued using the “value of a statistical life” (VSL), which is the sum of what people would pay to reduce their risk of dying by small amounts that together add up to one statistical life.30 In order to preliminarily estimate the health damage cost of Nr emission for China, in this study, we first used population density to estimate the exposures per unit Nr emissions; second, the WTP of air pollution mortality (indicated as VSL) was used to translate the exposures per unit Nr emissions to a final health damage cost. The calculations are as follows: HDCost i , k = HDCost j , k ·
VSLi f (pdi , k) · VSLj f (pdj , k)
(1)
3
Total Cost i =
∑ (HDCost i ,k ·Total Nr emissioni ,k) k=1
(2)
where HDCosti,k is the health damage cost per unit of Nr species k (NH3, NOx, N2O) emission in country i, VSLi is the VSL of air pollution mortality in country i, f(pdi,k) is the function of human health damage cost per unit of Nr species k emission related to population density in country i, pdi is population density in country i, Total Costi is the total health damage cost, and Total Nr emissioni,k is the total emission of Nr species k in country i. More details of parameters in eqs 1 and 2 can be seen in the Supporting Information (Figure S1, Table S7).
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RESULTS AND DISCUSSION Comparisons with Other Estimates on Chinese Emissions. Our estimate of Chinese NH3 emission (10.9 Tg N in 2005) is close to the averages of previous estimates (10.9 Tg N in 2005) (Figure 2, Table 1), is similar to IIASA (10.6 Tg Table 1. Estimates of Emission of NH3, NOx, and N2O in China in 2005 (Tg N) studies
methodsa
sourcesb
NH3
NOx
N2O
EDGAR, 2011
BU-TB
8.4
5.1
1.0
IIASA, 2011 Wang et al., 200933 Klimont et al., 200935 Zhang et al., 200949 this study
BU-TB BU
FF + IN + AG + WA + FR FF + IN + AG + WA AG + IN
10.6 13.4
5.2
1.2
BU-TB
FF + IN + AG + WA
5.1
BU-TB
FF + AG
5.9
BU-MB
FF + IN + AG + WA + FR + UG
10.9
5.3
1.0
a
BU = bottom-up emission inventory; BU-TB = bottom-up technology-based emission inventory; BU-MB = bottom-up mass balance based emission inventory. bFF = fossil fuel; IN = industrial; AG = agriculture; WA = wastewater and solid waste treatment; FR = forest; UG = urban greenland. 9423
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Figure 3. Spatial patterns of NH3, NOx, and N2O emission across China. (a) NH3; (b) N2O; (c) NOx from ground data; (d) NOx from satellite data; (e) correlation of NOx fluxes between ground data and satellite data. For NH3 and N2O, the spatial allocation was based on a 1 km resolution land use map. For NOx, ground data was aggregated to provincial levels, since over 90% of the NOx emissions were derived from human settlements that only occupied less than 3% of China’s territory.
China will contribute even more NOx emission to the global NOx budget if no regulations are implemented. N2O emission displayed a linear trend of continuous increase since 1980 and more than doubled by 2008 (Figure 2e), different from those of NH3 and NOx. The annual variations can be attributed largely (∼90%) to the increases in nitrogen flux from agriculture, forest and grassland, and surface water (Supporting Information, Figure S2), and the rest mainly attributes to fossil fuel combustion (∼6%), wastewater treatment (3%), and industrial processes (∼1%). The recent increases of nitrogen deposition and eutrophication contribute to the N2O emission from forest and grassland, and surface water, respectively.7,42 Currently, the N2O emission in China has reached 1.1 Tg N yr−1, accounting for 25% of the global N2O budget.43 Tian et al.7 suggested that N2O emissions have offset approximately half of the terrestrial CO2 sink in China during 1961−2005, leading to the enhancement of vectors for infectious diseases and the increased frequency of infestations.4,43 Considering the accelerating trend of total nitrogen flux in China,44 the projection of N2O emissions suggests a further increase. Spatial Variations and Causes. A provincial and land use breakdown of the reactive nitrogen emissions reveals
trajectory of NH3 emission for developed countries suggests that China may also reduce NH3 emission in the near future by adopting appropriate management practices for agriculture. NOx emissions from fossil fuel combustion in developed countries have been significantly reduced since the1980s,3,14 whereas the increase in NOx emission from developing countries has led to a relatively constant global NOx emission level.2 In China, NOx increased by 1.5 fold from 1980 to 1995 as Chinese GDP increased with an annual growth rate of 10% of during that period.35 As one of the results of the Asian economic crisis, the emissions decreased subsequently until 2000 with a turning point of NOx emission in 1996. The consumption of coal to total energy consumption decreased from 77% to 71% (calculated on the metric of energy), also contributing to the reduction of NOx emission from 1996 to 2000.18,36 After 2000, as the result of economic recovery, the NOx emission rose significantly and almost doubled (Figure 2c) with coal consumption nearly doubling from 2001 to 2008.36 China now contributes over a quarter to global NOx emission via fossil fuel combustion. Given the continuous increase of energy consumption in China, coal will still play an important role in energy supply in the future.41 In other words, 9424
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Figure 4. Summary of health damage costs by nitrogen emission among different subsystems and functional groups across China in 2008. Arrow colors: black = nitrogen fluxes to water bodies; green = N2O; gray = nitrogen deposition; orange = NH3; red = NOx. The colors of the backgrounds represent different functional groups: blue = life-supporter; green = processor; red = consumer; gray = remover. Units of the damage costs are billions of US dollars. Urban greenland was reassigned to the consumer group owing to its close relationship with the human and pet subsystem as well as its nonproduct supply services.
(mean annual temperature and precipitation) do not significantly affect the NOx emission in China (Supporting Information, Figure S4, p > 0.05). To test how local Nr emissions affect the atmospheric Nr concentration, the tropospheric columns of NO2 data were aggregated at the provincial level. The results show that the bottom-up inventories of NOx emission can explain over 75% of satellite measurements on tropospheric columns of NO2 (Figure 3e, R2 = 0.75, p < 0.001). N2O is largely biogenic and derived from agricultural soils, manure management,43 as well as forest soils, surface water and wastewater treatment,10 with these together accounting for 93% of all N2O fluxes in China (Supporting Information, Figure S3), compared to the value of 74% in Europe.45 The agricultural sector is the main source of biogenic N2O emission, followed by forest and surface water. We find agriculture dominated regions, such as the North China Plain, Lianghu Plain (in Hubei and Hunan provinces), Yangtze River Delta, and Pearl River Delta, have higher N2O emissions than other regions (Figure 3b). Such a spatial pattern is affected both by natural and socioeconomic factors (Supporting Information, Figure S4, R2 = 0.22−0.88, p < 0.01−0.001). It is because the high temperature and humidity can enhance the activities of microorganisms (e.g., nitrification and denitrification) that promote the biogenic N2O emission,46 meanwhile human activities increase the Nr inputs that can also enhance the activities of microorganisms.19,20 The proportions of nonbiogenic sources of N2O emission vary across China with higher values in relatively developed areas, such as 54% in Shanghai because the nonbiogenic sources of N2O mainly are fossil fuel combustion and industrial processes; in the contrary, this value is only 3% for less developed Tibet. Health Damage Cost Estimates by Emission. Emissions of NH3, NOx, and N2O lead to a number of negative effects to human health,47 mainly through the actions of secondary
considerable spatial heterogeneity across China (Figure 3). With about 95% of NH3 emissions originating from the agriculture sector (Supporting Information, Figure S3), human activities (as population density) dominate the NH3 emission in China (Supporting Information, Figure S4, R2 =0.91, p < 0.001). The contribution of agriculture is rather stable across the 31 provinces (Supporting Information, Figure S3). Precipitation and temperature also affect NH3 emission (Supporting Information, Figure S4, R2 = 0.27−0.41, p < 0.01) across China. High NH3 volatilization from manure and mineral fertilizer32 resulted in hotspots (a nitrogen hotspot is a small area with high Nr flux, 38) of NH3 fluxes where the livestock density and fertilizer application rate are high, in the North China Plain, South Central China, and Jiangsu and Guangdong provinces (Figure 3a). NH3 emissions from these hotspots (>100 kg N ha−1 yr−1) are about 10 times that of the nonhotspot (
